irt2p: Fitting Two Parameter Logistic Model

In nando11235813/raschreg: Item Response Theory models including explanatory variables of the ability parameter

Description

Estimate the two parameter logistic model approximating the marginal log-likelihood using Laplace approximation.

Usage

irt2p(items, init = NULL, fixed = NULL)

Arguments

items	Numeric matrix (or data.frame) containing only zeroes and ones (J columns).
init	Optional numeric vector of initial values at which initialize numerical optimization (length 2*J).
fixed	Optional numeric vector (length 2*J). If supplied, only NA entries in fixed will be estimated.

Details

Optimizes irt2plikLA numericaly via nlminb. Rows containing at least one NA are removed from items. Standard errors of model parameters are approximated by inverting the observed information matrix.

Value

An object of class rasch is a list containing the following componentes:

call	The matched call
coef	A named vector of coefficients
iter	Number of iterations used to optimize de log-likelihood
loglik	The log-likelihood value
vcov	The variance-covariance matrix of the estimated parameters
items	The item matrix
beta	(Only when regression terms are included) the estimated regression parameters
linpred	(Only when regression terms are included) prediction covariates

Author(s)

Fernando Massa, [e-mail]

References

\insertRef

baker2004raschreg

See Also

rasch, raschd, raschreg, raschdreg, irt2preg

Examples

n   <- 100
J   <- 7
X   <- sim_rasch(n, alpha = runif(J, 0.5, 1.5))
mod <- irt2p(X)

nando11235813/raschreg documentation built on Oct. 2, 2021, 3:11 p.m.